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06/27/2023
FLuRKA: Fast fused Low-Rank Kernel Attention
Many efficient approximate self-attention techniques have become prevale...
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06/27/2023
Input-sensitive dense-sparse primitive compositions for GNN acceleration
Graph neural networks (GNN) have become an important class of neural net...
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03/28/2023
Dias: Dynamic Rewriting of Pandas Code
In recent years, dataframe libraries, such as pandas have exploded in po...
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02/14/2023
COMET: X86 Cost Model Explanation Framework
ML-based program cost models have been shown to yield fairly accurate pr...
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10/08/2022
GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation
Analytical hardware performance models yield swift estimation of desired...
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10/08/2020
DiffTune: Optimizing CPU Simulator Parameters with Learned Differentiable Surrogates
CPU simulators are useful tools for modeling CPU execution behavior. How...
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08/03/2020
A Learned Performance Model for Tensor Processing Units
Accurate hardware performance models are critical to efficient code gene...
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02/07/2019
Revec: Program Rejuvenation through Revectorization
Modern microprocessors are equipped with Single Instruction Multiple Dat...
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08/21/2018
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks
Statically estimating the number of processor clock cycles it takes to e...
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04/23/2018
